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Evidence for the vitamin K-dependent gamma-carboxylation of the first glutamic acid residue in peptide substrates containing a diglutamyl sequence.

ABSTRACT: The peptide substrate commonly used in vitamin K-dependent carboxylation, Phe-Leu-Glu-Glu-Val, has been shown, by the use of high-voltage paper electrophoresis, to be degraded from the N-terminus by a microsomal leucine amino-peptidase. The replacement of phenylalanine with a N-t-butoxycarbonyl group resulted in a tetrapeptide substrate with a blocked N-terminus resistant to enzymic degradation. Vitamin K-dependent carboxylation of this non-degradable substrate gave a unique carboxylated product, which was separated from microsomal protein and unchanged substrate by using DEAE-Sephadex A25 as a final step. The carboxylated product was subsequently decarboxylated in 2HCl and analysed by using g.l.c. coupled to a mass spectrometer. This showed that only the first glutamic acid residue in the peptide substrate was carboxylated.

SUBMITTER: Burgess AI

PROVIDER: S-EPMC1152365 | biostudies-other | 1983 Oct

REPOSITORIES: biostudies-other

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Project description:BackgroundCarboxylation is a modification of glutamate (Glu) residues which occurs post-translation that is catalyzed by γ-glutamyl carboxylase in the lumen of the endoplasmic reticulum. Vitamin K is a critical co-factor in the post-translational conversion of Glu residues to γ-carboxyglutamate (Gla) residues. It has been shown that the process of carboxylation is involved in the blood clotting cascade, bone growth, and extraosseous calcification. However, studies in this field have been limited by the difficulty of experimentally studying substrate site specificity in γ-glutamyl carboxylation. In silico investigations have the potential for characterizing carboxylated sites before experiments are carried out.ResultsBecause of the importance of γ-glutamyl carboxylation in biological mechanisms, this study investigates the substrate site specificity in carboxylation sites. It considers not only the composition of amino acids that surround carboxylation sites, but also the structural characteristics of these sites, including secondary structure and solvent-accessible surface area (ASA). The explored features are used to establish a predictive model for differentiating between carboxylation sites and non-carboxylation sites. A support vector machine (SVM) is employed to establish a predictive model with various features. A five-fold cross-validation evaluation reveals that the SVM model, trained with the combined features of positional weighted matrix (PWM), amino acid composition (AAC), and ASA, yields the highest accuracy (0.892). Furthermore, an independent testing set is constructed to evaluate whether the predictive model is over-fitted to the training set.ConclusionsIndependent testing data that did not undergo the cross-validation process shows that the proposed model can differentiate between carboxylation sites and non-carboxylation sites. This investigation is the first to study carboxylation sites and to develop a system for identifying them. The proposed method is a practical means of preliminary analysis and greatly diminishes the total number of potential carboxylation sites requiring further experimental confirmation.

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Evidence for the vitamin K-dependent gamma-carboxylation of the first glutamic acid residue in peptide substrates containing a diglutamyl sequence.

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